Ephrin stimulation modulates T?cell chemotaxis
Bibliographic record
Abstract
Eph receptor tyrosine kinases and their ligands, the ephrins, are known to play an important role in regulating cell migration and targeting in neuronal and endothelial cells. Recently, it has been shown that lymphoid cells also express Eph receptors, raising the possibility that Eph receptors may similarly regulate lymphocyte migration. Chemotaxis in response to soluble chemokine factors is an essential facet of T cell biology. We demonstrate here that T cell chemotaxis in response to both the stromal cell-derived factor (SDF)-1alpha and macrophage inflammatory protein 3beta chemokines is modulated by costimulation with ephrins. Both ephrin-A and ephrin-B ligands were found to modify the chemotactic responses of a T cell line and primary T cells. Ephrin-A1, in particular, strongly inhibited chemotaxis. In accordance with the tyrosine kinase activity of EphA receptors, ephrin-A1 stimulation induced rapid intracellular tyrosine phosphorylation in T cells. Although strongly inhibiting chemotaxis, ephrin-A1 costimulus did not affect many of the signaling events downstream of the SDF-1alpha receptor CXCR4, including calcium flux and activation of MAPK. Rather, ephrin-A1 altered the balance of small G protein activity in T cells. Ephrin-A1 stimulation prevented SDF-1alpha-induced activation of cdc42, while simultaneously inducing rho activation. Ultimately, ephrin-A1 was found to inhibit chemokine-induced actin polymerization, thereby blocking migration. Ubiquitous ephrin expression in vivo creates enormous potential for T cells to encounter these ligands, suggesting that Eph receptors and ephrins may be important regulators of T cell migration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".